Survival of early-stage HGSOC by race
##
## Pairwise comparisons using Log-Rank test
##
## data: HGS.ES and Race
##
## White Black Hispanic API
## Black 0.00099 - - -
## Hispanic 0.88561 0.03049 - -
## API 0.88561 0.08697 0.88561 -
## Native 0.88561 0.51590 0.88561 0.88561
##
## P value adjustment method: BH
|
Race
|
Count
|
|
White
|
795
|
|
Black
|
60
|
|
Hispanic
|
111
|
|
API
|
76
|
|
Native
|
7
|
Comparing Black Race to All Other Races Combined
|
Black Race
|
Count
|
|
no
|
992
|
|
yes
|
60
|
## Call:
## coxph(formula = Surv(SurvMonths, COD) ~ Black.Race, data = HGS.ES)
##
## n= 1052, number of events= 177
##
## coef exp(coef) se(coef) z Pr(>|z|)
## Black.Raceyes 0.9013 2.4628 0.2377 3.792 0.00015 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## exp(coef) exp(-coef) lower .95 upper .95
## Black.Raceyes 2.463 0.406 1.546 3.924
##
## Concordance= 0.527 (se = 0.011 )
## Likelihood ratio test= 11.44 on 1 df, p=7e-04
## Wald test = 14.38 on 1 df, p=1e-04
## Score (logrank) test = 15.38 on 1 df, p=9e-05
Comparing Black Race to White Race
|
Race
|
Count
|
|
White
|
795
|
|
Black
|
60
|
## Call:
## coxph(formula = Surv(SurvMonths, COD) ~ Race, data = HGS.WB)
##
## n= 855, number of events= 147
##
## coef exp(coef) se(coef) z Pr(>|z|)
## RaceBlack 0.9082 2.4798 0.2409 3.77 0.000164 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## exp(coef) exp(-coef) lower .95 upper .95
## RaceBlack 2.48 0.4033 1.546 3.977
##
## Concordance= 0.533 (se = 0.013 )
## Likelihood ratio test= 11.41 on 1 df, p=7e-04
## Wald test = 14.21 on 1 df, p=2e-04
## Score (logrank) test = 15.21 on 1 df, p=1e-04
Comparing Black Race to Hispanic Race
|
Race
|
Count
|
|
Hispanic
|
111
|
|
Black
|
60
|
## Call:
## coxph(formula = Surv(SurvMonths, COD) ~ Race, data = HGS.HB)
##
## n= 171, number of events= 37
##
## coef exp(coef) se(coef) z Pr(>|z|)
## RaceBlack 0.8791 2.4088 0.3304 2.66 0.00781 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## exp(coef) exp(-coef) lower .95 upper .95
## RaceBlack 2.409 0.4152 1.26 4.603
##
## Concordance= 0.596 (se = 0.044 )
## Likelihood ratio test= 7.02 on 1 df, p=0.008
## Wald test = 7.08 on 1 df, p=0.008
## Score (logrank) test = 7.54 on 1 df, p=0.006
Does the addition of chemotherapy in patients with unknown nodal status improve outcomes in different races?
Black Race
|
Positive Nodes
|
Count
|
|
No
|
28
|
|
Unk
|
14
|
## Call:
## coxph(formula = Surv(SurvMonths, COD) ~ Nodes_Pos, data = HGS.ES.Black.Chemo)
##
## n= 42, number of events= 13
##
## coef exp(coef) se(coef) z Pr(>|z|)
## Nodes_PosUnk 2.218 9.188 0.701 3.164 0.00156 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## exp(coef) exp(-coef) lower .95 upper .95
## Nodes_PosUnk 9.187 0.1088 2.326 36.3
##
## Concordance= 0.706 (se = 0.07 )
## Likelihood ratio test= 11.7 on 1 df, p=6e-04
## Wald test = 10.01 on 1 df, p=0.002
## Score (logrank) test = 13.98 on 1 df, p=2e-04
White Race
|
Positive Nodes
|
Count
|
|
No
|
454
|
|
Unk
|
126
|
## Call:
## coxph(formula = Surv(SurvMonths, COD) ~ Nodes_Pos, data = HGS.ES.White.Chemo)
##
## n= 580, number of events= 82
##
## coef exp(coef) se(coef) z Pr(>|z|)
## Nodes_PosUnk 1.1643 3.2036 0.2237 5.206 1.93e-07 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## exp(coef) exp(-coef) lower .95 upper .95
## Nodes_PosUnk 3.204 0.3122 2.067 4.966
##
## Concordance= 0.637 (se = 0.028 )
## Likelihood ratio test= 24.43 on 1 df, p=8e-07
## Wald test = 27.1 on 1 df, p=2e-07
## Score (logrank) test = 30.28 on 1 df, p=4e-08
Hispanic Race
|
Positive Nodes
|
Count
|
|
No
|
63
|
|
Unk
|
18
|
## Call:
## coxph(formula = Surv(SurvMonths, COD) ~ Nodes_Pos, data = HGS.ES.Hisp.Chemo)
##
## n= 81, number of events= 12
##
## coef exp(coef) se(coef) z Pr(>|z|)
## Nodes_PosUnk 1.3209 3.7468 0.5787 2.282 0.0225 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## exp(coef) exp(-coef) lower .95 upper .95
## Nodes_PosUnk 3.747 0.2669 1.205 11.65
##
## Concordance= 0.67 (se = 0.074 )
## Likelihood ratio test= 4.87 on 1 df, p=0.03
## Wald test = 5.21 on 1 df, p=0.02
## Score (logrank) test = 6 on 1 df, p=0.01
Does use of chemotherapy matter by stage for each race?
Black Race
|
Chemotherapy received
|
Count
|
|
No/Unknown
|
15
|
|
Yes
|
28
|
## Call:
## coxph(formula = Surv(SurvMonths, COD) ~ Chemo, data = HGS.Black.N0)
##
## n= 43, number of events= 9
##
## coef exp(coef) se(coef) z Pr(>|z|)
## ChemoYes -0.3277 0.7206 0.6726 -0.487 0.626
##
## exp(coef) exp(-coef) lower .95 upper .95
## ChemoYes 0.7206 1.388 0.1928 2.693
##
## Concordance= 0.558 (se = 0.089 )
## Likelihood ratio test= 0.23 on 1 df, p=0.6
## Wald test = 0.24 on 1 df, p=0.6
## Score (logrank) test = 0.24 on 1 df, p=0.6
|
Chemotherapy received
|
Count
|
|
No/Unknown
|
3
|
|
Yes
|
14
|
## Call:
## coxph(formula = Surv(SurvMonths, COD) ~ Chemo, data = HGS.Black.Nx)
##
## n= 17, number of events= 11
##
## coef exp(coef) se(coef) z Pr(>|z|)
## ChemoYes -0.6283 0.5335 0.7016 -0.896 0.37
##
## exp(coef) exp(-coef) lower .95 upper .95
## ChemoYes 0.5335 1.874 0.1349 2.11
##
## Concordance= 0.595 (se = 0.095 )
## Likelihood ratio test= 0.73 on 1 df, p=0.4
## Wald test = 0.8 on 1 df, p=0.4
## Score (logrank) test = 0.83 on 1 df, p=0.4
White Race
|
Chemotherapy received
|
Count
|
|
No/Unknown
|
144
|
|
Yes
|
454
|
## Call:
## coxph(formula = Surv(SurvMonths, COD) ~ Chemo, data = HGS.White.N0)
##
## n= 598, number of events= 71
##
## coef exp(coef) se(coef) z Pr(>|z|)
## ChemoYes -0.3828 0.6820 0.2521 -1.519 0.129
##
## exp(coef) exp(-coef) lower .95 upper .95
## ChemoYes 0.682 1.466 0.4161 1.118
##
## Concordance= 0.538 (se = 0.029 )
## Likelihood ratio test= 2.2 on 1 df, p=0.1
## Wald test = 2.31 on 1 df, p=0.1
## Score (logrank) test = 2.33 on 1 df, p=0.1
|
Chemotherapy received
|
Count
|
|
No/Unknown
|
71
|
|
Yes
|
126
|
## Call:
## coxph(formula = Surv(SurvMonths, COD) ~ Chemo, data = HGS.White.Nx)
##
## n= 197, number of events= 56
##
## coef exp(coef) se(coef) z Pr(>|z|)
## ChemoYes -0.05535 0.94615 0.27660 -0.2 0.841
##
## exp(coef) exp(-coef) lower .95 upper .95
## ChemoYes 0.9461 1.057 0.5502 1.627
##
## Concordance= 0.516 (se = 0.035 )
## Likelihood ratio test= 0.04 on 1 df, p=0.8
## Wald test = 0.04 on 1 df, p=0.8
## Score (logrank) test = 0.04 on 1 df, p=0.8
Hispanic
|
Chemotherapy received
|
Count
|
|
No/Unknown
|
20
|
|
Yes
|
63
|
## Call:
## coxph(formula = Surv(SurvMonths, COD) ~ Chemo, data = HGS.Hisp.N0)
##
## n= 83, number of events= 8
##
## coef exp(coef) se(coef) z Pr(>|z|)
## ChemoYes 0.04951 1.05076 0.81854 0.06 0.952
##
## exp(coef) exp(-coef) lower .95 upper .95
## ChemoYes 1.051 0.9517 0.2112 5.227
##
## Concordance= 0.516 (se = 0.072 )
## Likelihood ratio test= 0 on 1 df, p=1
## Wald test = 0 on 1 df, p=1
## Score (logrank) test = 0 on 1 df, p=1
|
Chemotherapy received
|
Count
|
|
No/Unknown
|
10
|
|
Yes
|
18
|
## Call:
## coxph(formula = Surv(SurvMonths, COD) ~ Chemo, data = HGS.Hisp.Nx)
##
## n= 28, number of events= 9
##
## coef exp(coef) se(coef) z Pr(>|z|)
## ChemoYes 0.3245 1.3834 0.7123 0.456 0.649
##
## exp(coef) exp(-coef) lower .95 upper .95
## ChemoYes 1.383 0.7229 0.3425 5.587
##
## Concordance= 0.607 (se = 0.057 )
## Likelihood ratio test= 0.21 on 1 df, p=0.6
## Wald test = 0.21 on 1 df, p=0.6
## Score (logrank) test = 0.21 on 1 df, p=0.6
Overall CoxPH and Forest plot
##
## Pairwise comparisons using Log-Rank test
##
## data: HGS.ES and Race.Group
##
## White Hispanic Black
## Hispanic 0.9608 - -
## Black 0.0006 0.0183 -
## Other 0.9608 0.9608 0.0273
##
## P value adjustment method: BH
|
Race
|
Count
|
|
White
|
795
|
|
Hispanic
|
111
|
|
Black
|
60
|
|
Other
|
86
|
## Call:
## coxph(formula = Surv(SurvMonths, COD) ~ Age + Stage + Laterality +
## Chemotherapy + Race + Lymphadenectomy, data = HGS.ES)
##
## n= 1052, number of events= 177
##
## coef exp(coef) se(coef) z Pr(>|z|)
## Age18-29 NA NA 0.00000 NA NA
## Age30-39 0.08918 1.09328 0.60561 0.147 0.882930
## Age40-49 -0.19998 0.81875 0.30870 -0.648 0.517110
## Age50-59 0.27356 1.31464 0.22660 1.207 0.227331
## Age70-79 0.74815 2.11308 0.23762 3.149 0.001641 **
## Age80+ 1.36213 3.90449 0.26696 5.102 3.35e-07 ***
## StageT1NxM0 0.99923 2.71619 0.17946 5.568 2.58e-08 ***
## LateralityLeft -0.20815 0.81209 0.19148 -1.087 0.277006
## LateralityRight -0.22285 0.80023 0.19534 -1.141 0.253931
## LateralityUnknown 0.02839 1.02880 0.52898 0.054 0.957198
## ChemotherapyYes 0.01677 1.01691 0.16413 0.102 0.918621
## RaceHispanic 0.14746 1.15889 0.26396 0.559 0.576401
## RaceBlack 0.89159 2.43901 0.24682 3.612 0.000304 ***
## RaceOther 0.20776 1.23091 0.29860 0.696 0.486573
## LymphadenectomyInadequate 0.17427 1.19038 0.20846 0.836 0.403158
## LymphadenectomyNone NA NA 0.00000 NA NA
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## exp(coef) exp(-coef) lower .95 upper .95
## Age18-29 NA NA NA NA
## Age30-39 1.0933 0.9147 0.3336 3.583
## Age40-49 0.8187 1.2214 0.4471 1.499
## Age50-59 1.3146 0.7607 0.8432 2.050
## Age70-79 2.1131 0.4732 1.3263 3.366
## Age80+ 3.9045 0.2561 2.3138 6.589
## StageT1NxM0 2.7162 0.3682 1.9108 3.861
## LateralityLeft 0.8121 1.2314 0.5580 1.182
## LateralityRight 0.8002 1.2496 0.5457 1.174
## LateralityUnknown 1.0288 0.9720 0.3648 2.901
## ChemotherapyYes 1.0169 0.9834 0.7372 1.403
## RaceHispanic 1.1589 0.8629 0.6908 1.944
## RaceBlack 2.4390 0.4100 1.5035 3.956
## RaceOther 1.2309 0.8124 0.6856 2.210
## LymphadenectomyInadequate 1.1904 0.8401 0.7911 1.791
## LymphadenectomyNone NA NA NA NA
##
## Concordance= 0.721 (se = 0.02 )
## Likelihood ratio test= 98.62 on 14 df, p=9e-15
## Wald test = 109.4 on 14 df, p=<2e-16
## Score (logrank) test = 124.1 on 14 df, p=<2e-16
## chisq df p
## Age 6.666 5 0.25
## Stage 3.826 1 0.05
## Laterality 3.235 3 0.36
## Chemotherapy 0.018 1 0.89
## Race 3.057 3 0.38
## Lymphadenectomy 0.894 1 0.34
## GLOBAL 19.295 14 0.15
## Warning: Removed 40 row(s) containing missing values (geom_path).
## Warning: Removed 177 rows containing missing values (geom_point).
## Warning: Removed 40 row(s) containing missing values (geom_path).
## Warning: Removed 40 row(s) containing missing values (geom_path).
## Warning: Removed 40 row(s) containing missing values (geom_path).
## Warning: Removed 177 rows containing missing values (geom_point).
## Warning: Removed 40 row(s) containing missing values (geom_path).
## Warning: Removed 40 row(s) containing missing values (geom_path).
## Warning: Removed 40 row(s) containing missing values (geom_path).
## Warning: Removed 177 rows containing missing values (geom_point).
## Warning: Removed 40 row(s) containing missing values (geom_path).
## Warning: Removed 40 row(s) containing missing values (geom_path).
## Warning: Removed 40 row(s) containing missing values (geom_path).
## Warning: Removed 177 rows containing missing values (geom_point).
## Warning: Removed 40 row(s) containing missing values (geom_path).
## Warning: Removed 40 row(s) containing missing values (geom_path).
## Warning: Removed 40 row(s) containing missing values (geom_path).
## Warning: Removed 177 rows containing missing values (geom_point).
## Warning: Removed 40 row(s) containing missing values (geom_path).
## Warning: Removed 40 row(s) containing missing values (geom_path).
## Warning: Removed 40 row(s) containing missing values (geom_path).
## Warning: Removed 177 rows containing missing values (geom_point).
## Warning: Removed 40 row(s) containing missing values (geom_path).
## Warning: Removed 40 row(s) containing missing values (geom_path).
